Cai Hong, Zhao Yan-Jie, Xing Xiaomeng, Tian Tengfei, Qian Wang, Liang Sixiang, Wang Zhe, Cheung Teris, Su Zhaohui, Tang Yi-Lang, Ng Chee H, Sha Sha, Xiang Yu-Tao
Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao Special Administrative Region, People's Republic of China.
Centre for Cognitive and Brain Sciences, University of Macau, Macao Special Administrative Region, People's Republic of China.
Nat Sci Sleep. 2022 Aug 4;14:1351-1362. doi: 10.2147/NSS.S367974. eCollection 2022.
A high proportion of clinicians experienced common anxiety, insomnia and depression during the COVID-19 pandemic. This study examined the item-level association of comorbid anxiety and insomnia symptoms among clinicians who suffered from depressive symptoms during the late stage of the COVID-19 pandemic using network analysis (NA).
Clinicians with depressive symptoms (with a Patients Health Questionnaire (PHQ-9) total score of 5 and above) were included in this study. Anxiety and insomnia symptoms were measured using the Generalized Anxiety Disorder Scale - 7-item (GAD-7) and Insomnia Severity Index (ISI), respectively. Network analysis was conducted to investigate the network structure, central symptoms, bridge symptoms, and network stability of these disturbances. Expected influence (EI) was used to measure the centrality of index.
Altogether, 1729 clinicians were included in this study. The mean age was 37.1 [standard deviation (SD)=8.04 years], while the mean PHQ-9 total score was 8.42 (SD=3.33), mean GAD-7 total score was 6.45 (SD=3.13) and mean ISI total score was 8.23 (SD=5.26). Of these clinicians, the prevalence of comorbid anxiety symptoms (GAD-7≥5) was 76.8% (95% CI 74.82-78.80%), while the prevalence of comorbid insomnia symptoms (ISI≥8) was 43.8% (95% CI: 41.50-46.18%). NA revealed that nodes ISI7 ("Interference with daytime functioning") (EI=1.18), ISI4 ("Sleep dissatisfaction") (EI=1.08) and ISI5 ("Noticeability of sleep problem by others") (EI=1.07) were the most central (influential) symptoms in the network model of comorbid anxiety and insomnia symptoms in clinicians. Bridge symptoms included nodes PHQ3 ("Sleep") (bridge EI=0.55) and PHQ4 ("Fatigue") (bridge EI=0.49). Gender did not significantly influence the network structure, but "having the experience of caring for COVID-19 patients" significantly influenced the network structure.
Central symptoms and key bridge symptoms identified in this NA should be targeted in the treatment and preventive measures for clinicians suffering from comorbid anxiety, insomnia and depressive symptoms during the late stage of the COVID-19 pandemic.
在新冠疫情期间，很大一部分临床医生经历了常见的焦虑、失眠和抑郁。本研究采用网络分析（NA）方法，考察了在新冠疫情后期出现抑郁症状的临床医生中，焦虑与失眠症状共病的条目水平关联。
本研究纳入了抑郁症状患者（患者健康问卷（PHQ - 9）总分≥5分）。焦虑和失眠症状分别采用广泛性焦虑障碍量表7项版（GAD - 7）和失眠严重程度指数（ISI）进行测量。进行网络分析以研究这些障碍的网络结构、核心症状、桥梁症状和网络稳定性。采用预期影响（EI）来衡量指标的中心性。
本研究共纳入1729名临床医生。平均年龄为37.1岁[标准差（SD）=8.04岁]，PHQ - 9平均总分8.42（SD = 3.33），GAD - 7平均总分6.45（SD = 3.13），ISI平均总分8.23（SD = 5.26）。在这些临床医生中，焦虑症状共病（GAD - 7≥5）的患病率为76.8%（95%置信区间74.82 - 78.80%），失眠症状共病（ISI≥8）的患病率为43.8%（95%置信区间：41.50 - 46.18%）。网络分析显示，在临床医生焦虑与失眠症状共病的网络模型中，节点ISI7（“干扰日间功能”）（EI = 1.18）、ISI4（“睡眠不满意”）（EI = 1.08）和ISI5（“他人注意到睡眠问题”）（EI = 1.07）是最核心（最具影响力）的症状。桥梁症状包括节点PHQ3（“睡眠”）（桥梁EI = 0.55）和PHQ4（“疲劳”）（桥梁EI = 0.49）。性别对网络结构无显著影响，但“有照顾新冠患者的经历”对网络结构有显著影响。
在新冠疫情后期，对于患有焦虑、失眠和抑郁症状共病的临床医生，本网络分析中确定的核心症状和关键桥梁症状应作为治疗和预防措施的目标。
